1. Field
The following description relates to a natural language processing (NLP) technology, and more specifically, to an apparatus and method for amending a language analysis error.
2. Description of the Related Art
A deep language analysis technology is needed for an accelerated intelligent service, but if a complex language analysis, such as question answering, machine translation, a dialogue system, is required, language processing may be performed using various language analysis methods that are different from each other depending on a purpose.
However, a language analysis technology being used in general employs a method of sequentially performing a plurality of detailed analysis steps. For example, the detailed language analysis steps that are complex may be sequentially performed, such as a morphological analysis, named-entity recognition, word sense disambiguation, parsing, semantic role labeling, coreference resolution, zero anaphora recovery, and dialogue processing.
However, if the detailed analysis steps are sequentially performed as such, each of the detailed analysis steps is to analyze the language by using the analysis result of the previous step as input. Accordingly, if an error occurs in one analysis step, errors may occur all in the following analysis steps. For example, when a morphological analysis is performed with respect to a sentence “John likes a bird that flies the sky”, if an error analysis on this sentence is performed, resulting in “John(proper noun) like(common verb)+s(plural suffix) a(indefinite article) bird(common noun) that(relative pronoun) fly(general noun)+-es(plural suffix) the(definite article) sky(common noun)”, which indicates that the verb “fly” is wrongly analyzed as the common noun “fly (an insect)”, its meaning is not found from the verb “fly”, but from the noun “fly (an insect)” in performing a word sense disambiguation analysis. In other words, due to the dependence on an analysis result from the previous step, the analysis performance cannot help declining in an analysis step, and the more previous steps existing, the worse performance degradation.
As a plan to overcome such a phenomenon, proposed is a method of acquiring an analysis result from each step, not using an analysis result from the previous step as before. However, since in such a method, it is required to perform not only the n-th analysis but the analysis information of all the first to n-th analysis steps in the n-th analysis step, it may increase a level of process difficulty of each step, thereby making its implementation difficult. Also, in a case of the 7-th step, the previous steps are six, so that devising an access method is almost impossible.
In another plan, using a plurality of analysis results having each different access method, the best result among the plurality of analysis results is selected by majority. However, regarding the same problem, it is required to build a plurality of systems by devising various access methods, and obtain a result by simultaneously operating the plurality of systems in parallel, thereby resulting in complexity in its implementation. Also, the result obtained by the majority determination cannot be considered to be always right, so its analysis result is less accurate.